package com.atguigu.day09;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple1;
import org.apache.flink.api.java.tuple.Tuple12;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.annotation.DataTypeHint;
import org.apache.flink.table.annotation.FunctionHint;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.functions.ScalarFunction;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;


import static org.apache.flink.table.api.Expressions.$;
import static org.apache.flink.table.api.Expressions.call;

public class Flink04_UDF_TableFun {
    public static void main(String[] args) {
        //1.获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        //2.从端口读取数据并转为WaterSensor
        SingleOutputStreamOperator<WaterSensor> waterSensorStream = env.socketTextStream("localhost", 9999)
                .map(new MapFunction<String, WaterSensor>() {
                    @Override
                    public WaterSensor map(String value) throws Exception {
                        String[] split = value.split(",");
                        return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
                    }
                });

        //3.获取表的执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        Table table = tableEnv.fromDataStream(waterSensorStream);

        //TODO 4.使用自定义函数查询数据

        //不注册直接使用
      /*  table.joinLateral(call(MyUDTF.class,$("id")))
//                .select($("id"),$("word"))
                .select($("id"),$("f0"))
                .execute()
                .print();*/

        //先注册再使用
        tableEnv.createTemporarySystemFunction("MyUDTF", MyUDTF.class);

        /*table.joinLateral(call("MyUDTF",$("id")))
//                .select($("id"),$("word"))
                .select($("id"),$("f0"))
                .execute()
                .print();*/


        tableEnv.executeSql("select " +
                " id," +
                " f0" +
                " from " +table+
                " left join lateral" +
                " table(MyUDTF(id))" +
                " on true" +
                "" +
                "").print();

    }

    //自定义一个函数，按照下滑线切分id的数据，切出多个值
//    @FunctionHint(output = @DataTypeHint("ROW<word String>"))
//    public static class MyUDTF extends TableFunction<Row>{
    public static class MyUDTF extends TableFunction<Tuple1<String>>{
        public void eval(String value){
            String[] strings = value.split("_");
            for (String s : strings) {
                collect(Tuple1.of(s));
            }
        }
    }
}
